Weighted mean by groups

I am trying to get the weighted mean of values by group id but I don't undersnatnd why my ouput (Mean) is a matrix and not a vector.

id = { 'a'; 'a'; 'b'; 'b'; 'c'; 'c'};
values = [1;2;3;4;5;6];
weights = [0.5;0.7;0.3;0.4;0.5;0.1];
exampletable = table(id, weights, values);

G = findgroups(exampletable.id);
wmean = @(w,v)w'.*mean(v);
Mean = splitapply(wmean, exampletable.weights, exampletable.values, G)

id = { 'a'; 'a'; 'b'; 'b'; 'c'; 'c'};

values = [1;2;3;4;5;6];

weights = [0.5;0.7;0.3;0.4;0.5;0.1];

exampletable = table(id, weights, values);

G = findgroups(exampletable.id);

wmean = @(w,v)w'.*mean(v);

Mean = splitapply(wmean, exampletable.weights, exampletable.values, G)

Answer 1

[dpb]

It's the wmean function definition that's doing it -- what you intended was

wmean = @(w,v)mean(w.*v);

trying that,

id = { 'a'; 'a'; 'b'; 'b'; 'c'; 'c'};
values = [1;2;3;4;5;6];
weights = [0.5;0.7;0.3;0.4;0.5;0.1];
exampletable = table(id, weights, values);

G = findgroups(exampletable.id);
Mean = splitapply(wmean, exampletable.weights, exampletable.values, G)

Mean = 3×1

0.9500 1.2500 1.5500

ADDENDUM

OBTW, you can do things like this without the explicit step of findgroups with groupsummary (or several other ways, as well)--

gmeans=groupsummary(exampletable,'id',wmean,{"weights","values"})

gmeans = 3×3 table
     id      GroupCount    fun1_weights_values
    _____    __________    ___________________

    {'a'}        2                0.95        
    {'b'}        2                1.25        
    {'c'}        2                1.55        

[Maximilian Schwarz]

Thanks!